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卓漢浩,李寅龍 진주산업대학교 1996 論文集 Vol.35 No.-
In this paper, applications of the multilayer neural networks to the control of flexible robot manipulators are considered. The multilayer neural network can be used to aproximate any continuous function to any desired degree of accuracy and the weights are updaed by Gradient Method. When the flexible manipulator is rotated by motor through the fixed end, the transverse vibration may occur. The motor torque should be controlled in such a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipulators so that it is arrested as soon as possible at the end of rotation. Accurate control of lightweight manipulators during the large changes in configuration common to robotic tasks requires dynamic models that describe both the rigidbody motions, and the flexural vibrations. Therefore, this paper derives a linear dynamic state-space model for a single link flexible robot manipulator and composed LQR controller and inverse dynamical neuro-controller. The effectiveness of the proposed control system was proved by computer simulation.